Echo planar imaging (“EPI”) is a widely deployed magnetic resonance imaging (“MRI”) pulse sequence designed for rapid imaging. EPI is used for its ability to essentially freeze motion and acquire time-series data that are can be used for functional, diffusion, perfusion, and permeability imaging. Despite its broad use in both clinical and research applications, EPI is vulnerable to intrinsic image artifacts such as geometric distortion and blurring. The severity of these artifacts increase with the total time required to sample a given image frame. Therefore, several techniques have been proposed to minimize the acquisition time of EPI.
One such strategy is to employ parallel imaging techniques to accelerate the acquisition by skipping a portion of the image encoding steps, which shortens the total acquisition time. The skipped data are then estimated through image reconstruction techniques (e.g., GRAPPA) that exploit the partially-redundant information acquired through the channels of RF receive coil arrays. While accelerated parallel imaging can reduce these image artifacts, the amount of acceleration is limited by the number of available channels in the array. Parallel imaging techniques are also disadvantaged by signal-to-noise penalties that are incurred because of the reduced signal averaging available in accelerated acquisitions and by the noise enhancement caused by the associated image reconstruction methods.
A classic method for reducing distortion and blurring in EPI is to divide the image into multiple interleaved segments and acquire these segments separately. Thus, instead of acquiring the entire image frame after one shot in one segment, these techniques acquire the image piecemeal over several shots. This approach results in less distortion and blurring because the acquisition time for each segment is reduced compared to a single-shot acquisition. Unfortunately, conventional multi-shot EPI has a long vulnerable period during which dynamic effects (e.g., patient motion and/or breathing) can cause strong artifacts, precluding its widespread use.
One strategy to reduce this motion vulnerability is to change the temporal order in which the segments (which are interleaved in k-space) are acquired using the Fast Low-Excitation Echo-planar Technique (“FLEET”). This technique acquires all segments of a given image slice consecutively in time in order to shorten this vulnerable period and make the acquisition more robust. Because this reordering leaves no time for signal to recover between shots in a given slice, proper use of the FLEET method either requires the segments to be acquired with constant, low flip angles (“CLFA”) or with a variable flip angle (“VFA”) schedule in which the flip angle progressively increases with each shot (based on the recovery time and the tissue longitudinal relaxation value). While the CLFA approach can provide robustness, it sacrifices image signal-to-noise ratio by up to 80 percent. This loss of sensitivity is acceptable in some applications (e.g., using CLFA-FLEET for the acquisition of secondary data including motion-robust calibration data for accelerated parallel imaging reconstruction techniques), but may not be acceptable in cases where the FLEET acquisition is used for the primary imaging in which maximal sensitivity is desirable.
The VFA approach also provides robustness, but is plagued by strong image artifacts caused by the distribution of longitudinal relaxation rates found in patients (i.e., when more than one tissue is present) and because slice profiles and through-plane image phase vary greatly with increasing flip angle. Increasing the flip angle of a standard excitation pulse by increasing its voltage and therefore the excitation field causes distortions of the slice profile and phase across the slice in a flip angle dependent way. This flip angle dependent phase shift has precluded the use of VFA-FLEET because the distinct phase imparted on each interleaved segment causes a phase modulation across k-space that leads to strong ghosting artifacts in the final image.